Super-resolution Optical Fluctuation Imaging Research Articles

A super-resolution ultrasound imaging method based on active-modulated super-resolution optical fluctuation imaging.

Super resolution ultrasound imaging (SR-US) methods including super-resolution optical fluctuation imaging (SOFI) have been successfully demonstrated to improve imaging performance of ultrasound (US). However, the imaging quality of US improved by conventional SOFI depends on the probability of microbubbles (MB) appearing in imaging regions. Current SOFI-based ultrasound imaging methods usually fix the probability of MBs, ignoring the effect of probability characteristics, leading to artifacts in high-order SOFI images. Inspired by active-modulated SOFI (AR-SOFI), in this paper, we propose a new method, termed as AR-SOFI-US, for further improving the performance of SR-US, which is achieved by effectively controlling the probabilities of MBs on an appropriate range. Through a series of numerical simulations, we compare the imaging resolution at differing MB probabilities and demonstrate that by controlling the probabilities of MBs when they appear in the imaging regions, incorporating the proposed AR-SOFI-US method, we can improve the spatial resolution of SR-US to a higher degree, especially for the high-order SOFI imaging results.

Spatially Resolving Size Effects on Diffusivity in Nanoporous Extracellular Matrix-like Materials with Fluorescence Correlation Spectroscopy Super-Resolution Optical Fluctuation Imaging.

It is well documented that the nanoscale structures within porous microenvironments greatly impact the diffusion dynamics of molecules. However, how the interaction between the environment and molecules influences the diffusion dynamics has not been thoroughly explored. Here, we show that fluorescence correlation spectroscopy super-resolution optical fluctuation imaging (fcsSOFI) can be used to accurately measure the diffusion dynamics of molecules within varying matrices such as nanopatterned surfaces and porous agarose hydrogels. Our data demonstrate the robustness of fcsSOFI, where it is possible not only to quantify the diffusion speeds of molecules in heterogeneous media but also to recover the matrix structure with resolution on the order of 100 nm. Using dextran molecules of varying sizes, we show that the diffusion coefficient is sensitive to the change in the molecular hydrodynamic radius. fcsSOFI images further reveal that smaller dextran molecules can freely move through the small pores of the hydrogel and report the detailed porous structure and local diffusion heterogeneities not captured by the average diffusion coefficient. Conversely, bigger dextran molecules are confined and unable to freely move through the hydrogel, highlighting only the larger pore structures. These findings establish fcsSOFI as a powerful tool to characterize spatial and diffusion information of diverse macromolecules within biorelevant matrices.

SOGO-SOFI, light-modulated super-resolution optical fluctuation imaging using only 20 raw frames for high-fidelity reconstruction

Taking advantage of the stochastic photoswitching of genetically encodable reversibly photoswitchable fluorescent proteins (RSFPs), super-resolution optical fluctuation imaging (SOFI) and its variant photochromic stochastic optical fluctuation imaging (pcSOFI) are valuable tools for wide field super-resolution (SR) imaging. Live-cell (pc)SOFI, which requires a small number of original frames to reconstruct an SR image, is prone to structural discontinuity artifacts and low spatial resolution. Herein, we developed a repeated synchronized on- and gradually off-switching SOFI (SOGO-SOFI) that maximized the photoswitching frequency of RSFPs by light modulation and required only 20 frames for high-quality reconstruction. Live-cell SOGO-SOFI imaging of the endoplasmic reticulum (ER) exhibited 10 times higher temporal resolution (100 fps) and fewer artifacts than pcSOFI. Moreover, a combination of SOGO-SOFI with Airyscan further increased the image contrast and the resolution of Airyscan by a factor of 1.5 from 140 nm to 91 nm. The capabilities of SOGO-SOFI were further demonstrated by dual-color imaging of nucleolar proteins in mammalian cells and deep imaging of ER structures in thick brain slices (20.6 µm).

Live-Cell SOFI Correlation with SMLM and AFM Imaging.

Standard optical imaging is diffraction-limited and lacks the resolving power to visualize many of the organelles and proteins found within the cell. The advent of super-resolution techniques overcame this barrier, enabling observation of subcellular structures down to tens of nanometers in size; however these techniques require or are typically applied to fixed samples. This raises the question of how well a fixed-cell image represents the system prior to fixation. Here we present the addition of live-cell Super-Resolution Optical Fluctuation Imaging (SOFI) to a previously reported correlative process using Single Molecule Localization Microscopy (SMLM) and Atomic Force Microscopy (AFM). SOFI was used with fluorescent proteins and low laser power to observe cellular ultrastructure in live COS-7 cells. SOFI-SMLM-AFM of microtubules showed minimal changes to the microtubule network in the 20 min between live-cell SOFI and fixation. Microtubule diameters were also analyzed through all microscopies; SOFI found diameters of 249 ± 68 nm and SMLM was 71 ± 33 nm. AFM height measurements found microtubules to protrude 26 ± 13 nm above the surrounding cellular material. The correlation of SMLM and AFM was extended to two-color SMLM to image both microtubules and actin. Two target SOFI was performed with various fluorescent protein combinations. rsGreen1-rsKAME, rsGreen1-Dronpa, and ffDronpaF-rsKAME fluorescent protein combinations were determined to be suitable for two target SOFI imaging. This correlative application of super-resolution live-cell and fixed-cell imaging revealed minimal artifacts created for the imaged target structures through the sample preparation procedure and emphasizes the power of correlative microscopy.

SOFFLFM: Super-resolution optical fluctuation Fourier light-field microscopy

Fourier light-field microscopy (FLFM) uses a microlens array (MLA) to segment the Fourier plane of the microscopic objective lens to generate multiple two-dimensional perspective views, thereby reconstructing the three-dimensional (3D) structure of the sample using 3D deconvolution calculation without scanning. However, the resolution of FLFM is still limited by diffraction, and furthermore, it is dependent on the aperture division. In order to improve its resolution, a super-resolution optical fluctuation Fourier light-field microscopy (SOFFLFM) was proposed here, in which the super-resolution optical fluctuation imaging (SOFI) with the ability of super-resolution was introduced into FLFM. SOFFLFM uses higher-order cumulants statistical analysis on an image sequence collected by FLFM, and then carries out 3D deconvolution calculation to reconstruct the 3D structure of the sample. The theoretical basis of SOFFLFM on improving resolution was explained and then verified with the simulations. Simulation results demonstrated that SOFFLFM improved the lateral and axial resolution by more than [Formula: see text] and 2 times in the second- and fourth-order accumulations, compared with that of FLFM.

Characterization of (bio)molecular diffusion in porous hydrogels using fluorescence correlation spectroscopy superresolution optical fluctuation imaging (fcsSOFI).

The nanoscale physicochemical structure of porous microenvironments affects the diffusion dynamics of molecules within them. Chemical interactions between the diffusing molecules and porous media can further significantly change diffusion. Fluorescence correlation spectroscopy super-resolution optical fluctuation imaging (fcsSOFI) has been successfully applied to measure biomolecular diffusion in simulated hydrogels of varying matrix densities. In this work, we extended fcsSOFI to systematically characterize the diffusion dynamics of different molecules with varying size and chemical properties in the water, as well as in complex matrices such as patterned nano surfaces and porous agarose hydrogel. Our data shows that fcsSOFI can quantitively measure diffusion rates in these heterogeneous media as well as resolve their pore structures with high resolution. Using neutral dextran molecules of different sizes, we show that the diffusion coefficient in agarose hydrogel decreases with increasing size. However, using proteins such as BSA and lysozyme, we show that diffusion is slower compared to the similar-sized dextran due to the interaction of the agarose hydrogel matrix with the charged surfaces of proteins. Currently, we are working on characterizing protein diffusion in a more complex extracellular matrix (ECM) using fcsSOFI.

Switching of Organic Fluorophores by Glycerol‐sulfite Interactions for Single‐Molecule Super‐Resolution Microscopy**

AbstractPhotoinduced off‐switching of organic fluorophores is used in super‐resolution microscopy to separate and localize single fluorescent molecules. However, this method typically relies on the use of complex imaging buffers that make use of enzymatic oxygen scavengers to remove oxygen and primary thiols to reversibly reduce excited fluorophores to a non‐fluorescent state. Here, we show that the interactions between sodium sulfite and glycerol can also be used for efficient switching of common organic fluorophores. The addition of glycerol to the imaging buffer allows us to tune the dye switching from intermittent fluorescence to the off‐state. We additionally show that sodium sulfite‐glycerol‐based buffers are especially useful for imaging at low laser illumination intensities in high‐refractive index solutions and samples embedded in agarose gel. This significantly simplifies the implementation of different super‐resolution microscopy modalities such as direct STochastic Optical Reconstruction Microscopy (dSTORM) and Super‐resolution Optical Fluctuation Imaging (SOFI).

Magnify is a universal molecular anchoring strategy for expansion microscopy

Expansion microscopy enables nanoimaging with conventional microscopes by physically and isotropically magnifying preserved biological specimens embedded in a crosslinked water-swellable hydrogel. Current expansion microscopy protocols require prior treatment with reactive anchoring chemicals to link specific labels and biomolecule classes to the gel. We describe a strategy called Magnify, which uses a mechanically sturdy gel that retains nucleic acids, proteins and lipids without the need for a separate anchoring step. Magnify expands biological specimens up to 11 times and facilitates imaging of cells and tissues with effectively around 25-nm resolution using a diffraction-limited objective lens of about 280 nm on conventional optical microscopes or with around 15 nm effective resolution if combined with super-resolution optical fluctuation imaging. We demonstrate Magnify on a broad range of biological specimens, providing insight into nanoscopic subcellular structures, including synaptic proteins from mouse brain, podocyte foot processes in formalin-fixed paraffin-embedded human kidney and defects in cilia and basal bodies in drug-treated human lung organoids.

Super-resolution fluorescence blinking imaging using compressive sensing

Super-resolution optical fluctuation imaging (SOFI) is an extensively used super-resolution (SR) imaging technique. The sample condition and imaging system are simpler than most SR systems, and the cusp-artifacts limit the resolution of high-order SOFI. To improve the resolution of SOFI, an alternative method is to improve the reconstruction algorithm. Here, compressive sensing (CS) is used in SOFI to improve its resolution. The detailed CS reconstruction algorithm is chosen as multiple measurement vector model sparse Bayesian learning (MSBL). We demonstrate that MSBL can achieve higher than threefold resolution improvement in simulation under certain conditions. The SOFI experiment analysis demonstrates that MSBL can improve the resolution about 2.5-fold compared with the diffraction limit. All results prove that MSBL has a higher resolving ability compared with other algorithms. Our results prove that CS is a broad applicability tool for most of the existing SR microscopy techniques and can be applied in 3D and live-cell SR fluorescence microscopy imaging in the future.

PySOFI: an open source Python package for SOFI

Super-resolution optical fluctuation imaging (SOFI) is a highly democratizable technique that provides optical super-resolution without requirement of sophisticated imaging instruments. Easy-to-use open-source packages for SOFI are important to support the utilization and community adoption of the SOFI method, they also encourage the participation and further development of SOFI by new investigators. In this work, we developed PySOFI, an open-source Python package for SOFI analysis that offers the flexibility to inspect, test, modify, improve, and extend the algorithm. We provide complete documentation for the package and a collection of Jupyter Notebooks to demonstrate the usage of the package. We discuss the architecture of PySOFI and illustrate how to use each functional module. A demonstration on how to extend the PySOFI package with additional modules is also included in the PySOFI package. We expect PySOFI to facilitate efficient adoption, testing, modification, dissemination, and prototyping of new SOFI-relevant algorithms.

Wide-Field Super-Resolution Optical Fluctuation Imaging through Dynamic Near-Field Speckle Illumination.

Stochastic optical fluctuation imaging (SOFI) generates super-resolution fluorescence images by emphasizing the positions of fluorescent emitters via statistical analysis of their on-and-off blinking dynamics. In SOFI with speckle illumination (S-SOFI), the diffraction-limited grain size of the far-field speckles prevents independent blinking of closely located emitters, becoming a hurdle to realize the full super-resolution granted by SOFI processing. Here, we present a surface-sensitive super-resolution technique exploiting dynamic near-field speckle illumination to bring forth the full super-resolving power of SOFI without blinking fluorophores. With our near-field S-SOFI technique, up to 2.8- and 2.3-fold enhancements in lateral spatial resolution are demonstrated with computational and experimental fluorescent test targets labeled with conventional fluorophores, respectively. Fluorescent beads separated by 175 nm are also super-resolved by near-field speckles of 150 nm grain size, promising sub-100 nm resolution with speckle patterns of much smaller grain size.

Improved Ultrasound Imaging Performance With Complex Cumulant Analysis.

Ultrasound localization microscopy (ULM) breaks the acoustic diffraction limit. However, the temporal resolution of ULM is relatively low because of a long data-acquisition time. Inspired by super-resolution optical fluctuation imaging (SOFI), in this paper, we propose a method for ultrasound imaging with improved imaging performance, which is achieved by using cumulant analysis. Specifically, to eliminate the axial oscillations, here, the cumulant analysis framework is extended, which is used to process the complex-valued analytic signals rather than the real-valued signals. The results from the numerical simulations and in vitro physical phantom experiments indicate that by generalizing cumulant analysis to complex-valued signals, a high imaging performance is achieved with an improvement of ∼35%-42% (lateral direction) and ∼41%-42% (axial direction) in the resolution compared with the temporal mean envelope image, in terms of full-width-half-max (FWHM). In particularly, the axial oscillations appearing in the real cumulant images are effectively eliminated by the complex cumulant analysis. Moreover, the proposed method can easily take advantage of SOFI. In the phantom experiment, a short data-acquisition time (∼2 sec) is enough to obtain the improved spatial resolution. The proposed method offers an implementation of US with high spatial resolution, fast data-acquisition speed, and axial oscillations removal characteristics. The method provides the potential in US imaging fast biological processes in vivo.

Correlative 3D microscopy of single cells using super-resolution and scanning ion-conductance microscopy

High-resolution live-cell imaging is necessary to study complex biological phenomena. Modern fluorescence microscopy methods are increasingly combined with complementary, label-free techniques to put the fluorescence information into the cellular context. The most common high-resolution imaging approaches used in combination with fluorescence imaging are electron microscopy and atomic-force microscopy (AFM), originally developed for solid-state material characterization. AFM routinely resolves atomic steps, however on soft biological samples, the forces between the tip and the sample deform the fragile membrane, thereby distorting the otherwise high axial resolution of the technique. Here we present scanning ion-conductance microscopy (SICM) as an alternative approach for topographical imaging of soft biological samples, preserving high axial resolution on cells. SICM is complemented with live-cell compatible super-resolution optical fluctuation imaging (SOFI). To demonstrate the capabilities of our method we show correlative 3D cellular maps with SOFI implementation in both 2D and 3D with self-blinking dyes for two-color high-order SOFI imaging. Finally, we employ correlative SICM/SOFI microscopy for visualizing actin dynamics in live COS-7 cells with subdiffraction-resolution.

Experimental Combination of Super-Resolution Optical Fluctuation Imaging with Structured Illumination Microscopy for Large Fields-of-View

Experimental Combination of Super-Resolution Optical Fluctuation Imaging with Structured Illumination Microscopy for Large Fields-of-View

Expansion Microscopy with Multifunctional Polymer Dots.

Expansion microscopy (ExM) provides nanoscale resolution on conventional microscopes via physically enlarging specimens with swellable polyelectrolyte gels. However, challenges involving fluorophore degradation and dilution during sample expansion have yet to be overcome. Herein, sequential cellular targeting, gel anchoring, and high-fidelity fluorescence reported using multifunctional polymer dots (Pdots) designed for ExM applications are demonstrated. The impressive brightness of the Pdots facilitates multicolor ExM, thereby enabling visualization of a variety of subcellular structures and neuron synapses. The average fluorescence intensities of Pdots in ExM range from ≈3 to 6 times higher than those achieved using commercially available Alexa dyes. Moreover, the fluorescence brightness and optical fluctuation are significantly improved by a surfactant-containing expansion buffer, which enables further resolution enhancement via super-resolution optical fluctuation imaging (SOFI). The combination of ExM and SOFI allows subcellular structures of ≈30nm to be resolved by conventional microscopes. These results highlight the immense potential of multifunctional Pdots for ExM-enhanced super-resolution imaging.

CSPARCOM: Multi-detector reconstruction by confocal super-resolution correlation microscopy.

Image scanning microscopy (ISM), an upgraded successor of the ubiquitous confocal microscope, facilitates up to two-fold improvement in lateral resolution, and has become an indispensable element in the toolbox of the bio-imaging community. Recently, super-resolution optical fluctuation image scanning microscopy (SOFISM) integrated the analysis of intensity-fluctuations information into the basic ISM architecture, to enhance its resolving power. Both of these techniques typically rely on pixel-reassignment as a fundamental processing step, in which the parallax of different detector elements to the sample is compensated by laterally shifting the point spread function (PSF). Here, we propose an alternative analysis approach, based on the recent high-performing sparsity-based super-resolution correlation microscopy (SPARCOM) method. Through measurements of DNA origami nano-rulers and fixed cells labeled with organic dye, we experimentally show that confocal SPARCOM (cSPARCOM), which circumvents pixel-reassignment altogether, provides enhanced resolution compared to pixel-reassigned based analysis. Thus, cSPARCOM further promotes the effectiveness of ISM, and particularly that of correlation based ISM implementations such as SOFISM, where the PSF deviates significantly from spatial invariance.

Smoothness correction for better SOFI imaging

Sub-diffraction or super-resolution fluorescence imaging allows the visualization of the cellular morphology and interactions at the nanoscale. Statistical analysis methods such as super-resolution optical fluctuation imaging (SOFI) obtain an improved spatial resolution by analyzing fluorophore blinking but can be perturbed by the presence of non-stationary processes such as photodestruction or fluctuations in the illumination. In this work, we propose to use Whittaker smoothing to remove these smooth signal trends and retain only the information associated to independent blinking of the emitters, thus enhancing the SOFI signals. We find that our method works well to correct photodestruction, especially when it occurs quickly. The resulting images show a much higher contrast, strongly suppressed background and a more detailed visualization of cellular structures. Our method is parameter-free and computationally efficient, and can be readily applied on both two-dimensional and three-dimensional data.

Design of experiments for the optimization of SOFI super-resolution microscopy imaging.

Super-resolution optical fluctuation imaging (SOFI) is a well-known super-resolution technique appreciated for its versatility and broad applicability. However, even though an extended theoretical description is available, it is still not fully understood how the interplay between different experimental parameters influences the quality of a SOFI image. We investigated the relationship between five experimental parameters (measurement time, on-time t on, off-time t off, probe brightness, and out of focus background) and the quality of the super-resolved images they yielded, expressed as Signal to Noise Ratio (SNR). Empirical relationships were modeled for second- and third-order SOFI using data simulated according to a D-Optimal design of experiments, which is an ad-hoc design built to reduce the experimental load when the total number of trials to be conducted becomes too high for practical applications. This approach proves to be more reliable and efficient for parameter optimization compared to the more classical parameter by parameter approach. Our results indicate that the best image quality is achieved for the fastest emitter blinking (lowest t on and t off), lowest background level, and the highest measurement duration, while the brightness variation does not affect the quality in a statistically significant way within the investigated range. However, when the ranges spanned by the parameters are constrained, a different set of optimal conditions may arise. For example, for second-order SOFI, we identified situations in which the increase of t off can be beneficial to SNR, such as when the measurement duration is long enough. In general, optimal values of t on and t off have been found to be highly dependent from each other and from the measurement duration.

Computationally-efficient spatiotemporal correlation analysis super-resolves anomalous diffusion.

Anomalous diffusion dynamics in confined nanoenvironments govern the macroscale properties and interactions of many biophysical and material systems. Currently, it is difficult to quantitatively link the nanoscale structure of porous media to anomalous diffusion within them. Fluorescence correlation spectroscopy super-resolution optical fluctuation imaging (fcsSOFI) has been shown to extract nanoscale structure and Brownian diffusion dynamics within gels, liquid crystals, and polymers, but has limitations which hinder its wider application to more diverse, biophysically-relevant datasets. Here, we parallelize the least-squares curve fitting step on a GPU improving computation times by up to a factor of 40, implement anomalous diffusion and two-component Brownian diffusion models, and make fcsSOFI more accessible by packaging it in a user-friendly GUI. We apply fcsSOFI to simulations of the protein fibrinogen diffusing in polyacrylamide of varying matrix densities and super-resolve locations where slower, anomalous diffusion occurs within smaller, confined pores. The improvements to fcsSOFI in speed, scope, and usability will allow for the wider adoption of super-resolution correlation analysis to diverse research topics.

Multi-Color, Bleaching-Resistant Super-Resolution Optical Fluctuation Imaging with Oligonucleotide-Based Exchangeable Fluorophores.

Super‐resolution optical fluctuation imaging (SOFI) is a super‐resolution microscopy technique that overcomes the diffraction limit by analyzing intensity fluctuations of statistically independent emitters in a time series of images. The final images are background‐free and show confocality and enhanced spatial resolution (super‐resolution). Fluorophore photobleaching, however, is a key limitation for recording long time series of images that will allow for the calculation of higher order SOFI results with correspondingly increased resolution. Here, we demonstrate that photobleaching can be circumvented by using fluorophore labels that reversibly and transiently bind to a target, and which are being replenished from a buffer which serves as a reservoir. Using fluorophore‐labeled short DNA oligonucleotides, we labeled cellular structures with target‐specific antibodies that contain complementary DNA sequences and record the fluctuation events caused by transient emitter binding. We show that this concept bypasses extensive photobleaching and facilitates two‐color imaging of cellular structures with SOFI.